Some of the terminology of statistics and epidemiology is not only confusing, but it is misleading. Consider the terms “effect size,” “random effects,” and “fixed effect,” which are all used to describe associations even if known to be non-causal. Biostatisticians and epidemiologists know that the terms are about putative or potential effects, but the sloppy, short-hand nomenclature can be misleading.
Although “risk” has a fairly precise meaning in scientific parlance, the usage for “risk factor” is fuzzy, loose, and imprecise. Journalists and plaintiffs’ lawyers use “risk factor,” much as they another frequently abused term in their vocabulary: “link.” Both “risk factor” and “link” sound as though they are “causes,” or at least as though they have something to do with causation. The reality is usually otherwise.
The business of exactly what “risk factor” means is puzzling and disturbing. The phrase seems to have gained currency because it is squishy and without a definite meaning. Like the use of “link” by journalists, the use of “risk factor” protects the speaker against contradiction, but appears to imply a scientifically valid conclusion. Plaintiffs’ counsel and witnesses love to throw this phrase around precisely because of its ambiguity. In journal articles, authors sometimes refer to any exposure inquired about in a case-control study to be a “risk factor,” regardless of the study result. So a risk factor can be merely an “exposure of interest,” or a possible cause, or a known cause.
The author’s meaning in using the phrase “risk factor” can often be discerned from context. When an article reports a case-control study, which finds an association with an exposure to some chemical the article will likely report in the discussion section that the study found that chemical to be a risk factor. The context here makes clear that the chemical was found to be associated with the outcome, and that chance was excluded as a likely explanation because the odds ratio was statistically significant. The context is equally clear that the authors did not conclude that the chemical was a cause of the outcome because they did not rule out bias or confounding; nor did they do any appropriate analysis to reach a causal conclusion and because their single study would not have justified reaching a causal association.
Sometimes authors qualify “risk factor” with an adjective to give more specific meaning to their usage. Some of the adjectives used in connection with the phrase include:
– putative, possible, potential, established, well-established, known, certain, causal, and causative
The use of the adjective highlights the absence of a precise meaning for “risk factor,” standing alone. Adjectives such as “established,” or “known” imply earlier similar findings, which are corroborated by the study at hand. Unless “causal” is used to modify “risk factor,” however, there is no reason to interpret the unqualified phrase to imply a cause.
Here is how the phrase “risk factor” is described in some noteworthy texts and treatises.
Legal Treatises
Professor David Faigman, and colleagues, with some understatement, note that the term “risk factor is loosely used”:
“Risk Factor An aspect of personal behavior or life-style, an environmental exposure, or an inborn or inherited characteristic, which on the basis of epidemiologic evidence is known to be associated with health-related condition(s) considered important to prevent. The term risk factor is rather loosely used, with any of the following meanings:
1. An attribute or exposure that is associated with an increased probability of a specified outcome, such as the occurrence of a disease. Not necessarily a causal factor.
2. An attribute or exposure that increases the probability of occurrence of disease or other specified outcome.
3. A determinant that can be modified by intervention, thereby reducing the probability of occurrence of disease or other specified outcomes.”
David L. Faigman, Michael J. Saks, Joseph Sanders, and Edward Cheng, Modern Scientific Evidence: The Law and Science of Expert Testimony 301, vol. 1 (2010)(emphasis added).
The Reference Manual on Scientific Evidence (2011) (RMSE3d) does not offer much in the way of meaningful guidance here. The chapter on statistics in the third edition provides a somewhat circular, and unhelpful definition. Here is the entry in that chapter’s glossary:
risk factor. See independent variable.
RMSE3d at 295. If the glossary defined “independent variable” as a simply a quantifiable variable that was being examined for some potential relationship with the outcome, or dependent, variable, the RMSE would have avoided error. Instead the chapter’s glossary, as well as its text, defines independent variables as “causes,” which begs the question why do a study to determine whether the “independent variable” is even a candidate for a causal factor? Here is how the statistics chapter’s glossary defines independent variable:
“Independent variables (also called explanatory variables, predictors, or risk factors) represent the causes and potential confounders in a statistical study of causation; the dependent variable represents the effect. ***. “
RMSE3d at 288. This is surely circular. Studies of causation are using independent variables that represent causes? There would be no reason to do the study if we already knew that the independent variables were causes.
The text of the RMSE chapter on statistics propagates the same confusion:
“When investigating a cause-and-effect relationship, the variable that represents the effect is called the dependent variable, because it depends on the causes. The variables that represent the causes are called independent variables. With a study of smoking and lung cancer, the independent variable would be smoking (e.g., number of cigarettes per day), and the dependent variable would mark the presence or absence of lung cancer. Dependent variables also are called outcome variables or response variables. Synonyms for independent variables are risk factors, predictors, and explanatory variables.”
FMSE3d at 219. In the text, the identification of causes with risk factors is explicit. Independent variables are the causes, and a synonym for an independent variable is “risk factor.” The chapter could have avoided this error simply by the judicious use of “putative,” or “candidate” in front of “causes.”
The chapter on epidemiology exercises more care by using “potential” to modify and qualify the risk factors that are considered in a study:
“In contrast to clinical studies in which potential risk factors can be controlled, epidemiologic investigations generally focus on individuals living in the community, for whom characteristics other than the one of interest, such as diet, exercise, exposure to other environmental agents, and genetic background, may distort a study’s results.”
FMSE3d at 556 (emphasis added).
Scientific Texts
Turning our attention to texts on epidemiology written for professionals rather than judges, we find that sometimes the term “risk factor” with a careful awareness of its ambiguity.
Herbert I. Weisberg is a statistician whose firm, Correlation Research Inc., specializes in the applied statistics in legal issues. Weisberg recently published an interesting book on bias and causation, which is recommended reading for lawyers who litigate claimed health effects. Weisberg’s book defines “risk factor” as merely an exposure of interest in a study that is looking for associations with a harmful outcome. He insightfully notes that authors use the phrase “risk factor” and similar phrases to avoid causal language:
“We will often refer to this factor of interest as a risk factor, although the outcome event is not necessarily something undesirable.”
Herbert I. Weisberg, Bias and Causation: Models and Judgment for Valid Comparisons 27 (2010).
“Causation is discussed elliptically if at all; statisticians typically employ circumlocutions such as ‘independent risk factor’ or ‘explanatory variable’ to avoid causal language.”
Id. at 35.
“Risk factor : The risk factor is the exposure of interest in an epidemiological study and often has the connotation that the outcome event is harmful or in some way undesirable.”
Id. at 317. This last definition is helpful in illustrating a balanced, fair definition that does not conflate risk factor with causation.
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Lemuel A. Moyé is an epidemiologist who testified in pharmaceutical litigation, mostly for plaintiffs. His text, Statistical Reasoning in Medicine: The Intuitive P-Value Primer, is in places a helpful source of guidance on key concepts. Moyé puts no stock in something’s being a risk factor unless studies show a causal relationship, established through a proper analysis. Accordingly, he uses “risk factor” to signify simply an exposure of interest:
“4.2.1 Association versus Causation
An associative relationship between a risk factor and a disease is one in which the two appear in the same patient through mere coincidence. The occurrence of the risk factor does not engender the appearance of the disease.
Causal relationships on the other hand are much stronger. A relationship is causal if the presence of the risk factor in an individual generates the disease. The causative risk factor excites the production of the disease. This causal relationship is tight, containing an embedded directionality in the relationship, i.e., (1) the disease is absence in the patient, (2) the risk factor is introduced, and (3) the risk factor’s presence produces the disease.
The declaration that a relationship is causal has a deeper meaning then the mere statement that a risk factor and disease are associated. This deeper meaning and its implications for healthcare require that the demonstration of a causal relationship rise to a higher standard than just the casual observation of the risk factor and disease’s joint occurrence.
Often limited by logistics and the constraints imposed by ethical research, the epidemiologist commonly cannot carry out experiments that identify the true nature of the risk factor–disease relationship. They have therefore become experts in observational studies. Through skillful use of observational research methods and logical thought, epidemiologists assess the strength of the links between risk factors and disease.”
Lemuel A. Moyé, Statistical Reasoning in Medicine: The Intuitive P-Value Primer 92 (2d ed. 2006)
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In A Dictionary of Epidemiology, which is put out by the International Epidemiology Association, a range of meanings is acknowledged, although the range is weighted toward causality:
“RISK FACTOR (Syn: risk indicator)
1. An aspect of personal behavior or lifestyle, an environmental exposure, or an inborn or inherited characteristic that, on the basis of scientific evidence, is known to be associated with meaningful health-related condition(s). In the twentieth century multiple cause era, a synonymous with determinant acting at the individual level.
2. An attribute or exposure that is associated with an increased probability of a specified outcome, such as the occurrence of a disease. Not necessarily a causal factor: it may be a risk marker.
3. A determinant that can be modified by intervention, thereby reducing the probability of occurrence of disease or other outcomes. It may be referred to as a modifiable risk factor, and logically must be a cause of the disease.
The term risk factor became popular after its frequent use by T. R. Dawber and others in papers from the Framingham study.346 The pursuit of risk factors has motivated the search for causes of chronic disease over the past half-century. Ambiguities in risk and in risk-related concepts, uncertainties inherent to the concept, and different legitimate meanings across cultures (even if within the same society) must be kept in mind in order to prevent medicalization of life and iatrogenesis.124–128,136,142,240”
Miquel Porta, Sander Greenland, John M. Last, eds., A Dictionary of Epidemiology 218-19 (5th ed. 2008). We might add that the uncertainties inherent in risk concepts should be kept in mind to prevent overcompensation for outcomes not shown to be caused by alleged tortogens.
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One introductory text uses “risk factor” as a term to describe the independent variable, while acknowledging that the variable does not become a risk factor until after the study shows an association between factor and the outcome of interest:
“A case-control study is one in which the investigator seeks to establish an association between the presence of a characteristic (a risk factor).”
Sylvia Wassertheil-Smoller, Biostatistics and Epidemiology: A Primer for Health and Biomedical Professionals 104 (3d ed. 2004). See also id. at 198 (“Here, also, epidemiology plays a central role in identifying risk factors, such as smoking for lung cancer”). Although it should be clear that much more must happen in order to show a risk factor is causally associated with an outcome, such as lung cancer, it would be helpful to spell this out. Some texts simply characterize risk factor as associations, not necessarily causal in nature. Another basic text provides:
“Analytical studies examine an association, i.e. the relationship between a risk factor and a disease in detail and conduct a statistical test of the corresponding hypothesis … .”
Wolfgang Ahrens & Iris Pigeot, eds., Handbook of Epidemiology 18 (2005). See also id. at 111 (Table describing the reasoning in a case-control study: “Increased prevalence of risk factor among diseased may indicate a causal relationship.”)(emphasis added).
These texts, both legal and scientific, indicate a wide range of usage and ambiguity for “risk factor.” There is a tremendous potential for the unscrupulous expert witness, or the uneducated lawyer, to take advantage of this linguistic latitude. Courts and counsel must be sensitive to the ambiguity and imprecision in usages of “risk factor,” and the mischief that may result. The Reference Manual on Scientific Evidence needs to sharpen and update its coverage of this and other statistical and epidemiologic issues.
